COMPARATIVE ANALYSIS OF AGRICULTURE ON THE EVE OF THE FORMATION OF OLD RUS’
Bibliographic record
Abstract
The article is a definite result of the study of agriculture of archeological cultures of the last quarter of the 1st millennium AD in the south of Eastern Europe, which became the basis for the formation of Old Rus’ material culture. The object of the study are archeological cultures, which were the basis and / or the place for the emergence of the Old Rus’ culture. They are the Borshevo culture on the Don, the Saltiv culture (mainly based on the materials of the Siversky-Donetsk region), the Volintseve and Romny sites (the left bank of the Dnieper), as well as the Raiky culture (the territory between the Dnieper and the Carpathians) (Fig. 1). The subject of the study are the components of agriculture (farming and livestock breeding) in these cultures.
 Nowadays the degree of research of these sectors allows us to conduct their comparative analysis and to determine the vectors of influences. The analysis of potential resource zones shows that ancient settlers at the time of settlement probably did not attach much importance to the surrounding lands, and gradually adapted them to their needs. According to the results of the analysis of the location of the Saltiv and Romny sites in the Siverskyi-Donetsk region contact area, we can say that the bearers of the Romny culture came to the resource zones already absorbed by the Saltiv people. Above all, this concerns the use of the land for agricultural purposes. We can offer a similar situation for bearers of the Raiky culture, which often continued to use the resource areas assimilated by their predecessors — the Prague culture bearers.
 Comparative analysis of agricultural implements (Fig. 2; 3) shows that the Saltiv culture bearers had a negligible positive influence on the spread of certain forms of tools of agricultural labor. Biological definitions and palaeoethnobotanical and archaeozoological analyzes (Fig. 4—6) are more likely to show insignificant differences in environmental conditions, as well as, possibly, in the ethnicity of ancient farmers. No influences of one culture on another were found on these materials. Probably, meat production among the population of the Saltiv culture has acquired certain forms of specialization because only in this culture such specific tools as cutting knives are known now (Fig. 7).
 The overall result may be the following. Among the comparable cultures, both branches of agriculture were the most developed among the bearers of the Saltiv culture. They had some influence on the development of agriculture among their neighbors — the Siverians and the Slavs on the Don. However, in all these cultures, the level of development of agriculture was approximately the same. It is not possible to take certain differences in livestock production for criteria of greater or lesser degree of development, since livestock production reflects most likely the ecological differences of settlements and the ethnic difference of settlers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".